Robot Arm Knows What You Want

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Scientists have invented a device that allows paralyzed patients
to control a robot arm directly from their brain, bypassing their
damaged central nervous system.

This brainwave-connected device would then be able to grab
objects that the user wants. The system uses tiny electrodes
implanted directly into the primary motor cortex, the part of the
brain that controls movement. Signals are then routed through a
tiny box in the scalp, which is then connected by wire to a small
refrigerator-size computer. The computer then translates the
brain movement patterns into an algorithm that can be transmitted
directly to the robot arm.

“The ultimate goal is to develop neural technologies to restore
mobility specifically for people with no control of their arms or
hands,” said Leigh Hochberg, a neurologist at the Department of
Veterans Affairs in Providence, R.I., who also has appointments
at Massachusetts General Hospital, Brown University and Harvard
University. “We’re hoping to provide technology directly from
brain signals back to commands that control assisted devices or
limbs.”

Hochberg and John Donoghue, director of the Brain Institute at
Brown, had previously collaborated on the “BrainGate” project
that produced the 2006 study showing how a patient could control
a computer cursor using a brain-to-computer neural interface.
Their latest study, which appears in today’s issue of the British
science journal Nature, goes a step further. It is, in effect,
developing a separate neural pathway to deliver messages from the
brain to an arm, in this case an artificial one.

Hochberg said the experiment has worked with two patients, a man
and a woman who both lost the use of their limbs and their voice
as a result of a stroke.

Both patients were able to move the robot arm to grab foam balls.
And the woman was able to pick up a metal coffee container and
drink through a straw for the first time since she was injured 15
years earlier.

“The smile on her face was something I and our research team will
never forget,” Hochberg said.

The researchers cautioned that the efforts with the two patients
only worked successfully about two-thirds of the time, and are
not as fast or accurate as a human arm. The experiment does give
hope to millions of patients who have become paralyzed as the
result of stroke or other physical trauma.

Researchers implanted an array of electrodes the size of a baby
aspirin near the top of the motor cortex. From their, 96
hair-thin electrodes pick up signals and send them to a
penny-sized device in the top of the scalp. A matchbox-sized
transmitter on top of the head then relays the brain signals to
the computer which controls the robot arm.

Each neuron is like a radio broadcast tower putting out signals
that generates a pattern, Donohue said.

“It’s like a QR code coming out at all times. The computer takes
that pattern and translates it into a command that moves it to
the left or right."

The next step is to rig the BrainGate system to a prosthetic
limbs that a patient could wear. And after that, perhaps to the
muscles in the paralyzed limbs themselves.The researchers
compared the development of their project to the years of
engineering and neuroscience used to develop cardiac pacemakers
and deep brain stimulators which are now used to help Parkinson’s
disease patients. At first these devices were experimental and
expensive, but are now common and affordable.

“There’s no doubt that for this device to be successful, it has
to reach people who would benefit and it will have to be
affordable,” Hochberg said.

“Affordable means that it’s in a range that can be acquired
privately or reimbursable by insurance.”

The BrainGate project is also leading to new understanding about
the capabilities of robots, according to Patrick van der Smagt, a
director of biomimetic robotics and machine learning labs at the
German Aerospace Center and the Technical University of Munich,
and a co-author on the Nature paper.

“We start to understand the properties of a muscle,” van der
Smagt said, “and we want to use that understanding to build
future robots more efficiently and more safely.”